####################################
Replication of “Assessing the Influence of Neutral Grounds on Match Outcomes.” 
Liam Kneafsey, and Stefan Müller
International Journal of Performance Analysis in Sport
####################################


Abstract: The home advantage in various sports has been well documented. So far, we lack knowledge whether playing in neutral venues indeed removes many, if not all, theoretically assumed advantages of playing at home. Analysing over 3,500 Gaelic football and hurling matches – field games with the highest participation rates in Ireland – between 2009 and 2018, we test the potential moderating influence of neutral venues. In hurling and Gaelic football, a considerable share of matches in played at neutral venues. We test the influence of neutral venues based on descriptive statistics, and multilevel logistic and multinomial regressions controlling for team strength, the importance of the match, the year, and the sport. With predicted probabilities ranging between 0.8 and 0.9, the favourite team is very likely to win home matches. The predicted probability drops below 0.6 for away matches. At neutral venues, the favourite team has a predicted probability of winning of 0.7. A Coarsened Exact Matching (CEM) approach also reveals very substantive and significant effects for the ‘treatment’ of neutral venues. Overall, neutral venues appear to be an under-utilised option for creating fairer and less predictable competition, especially in single-game knock-out matches.


Information on the Replication Material

Please open the file neutral_grounds_ijpas.Rproj and run the following script to reproduce the results.

* replicate_kneafsey_mueller_ijpas.R: reproduces all regression models, plots, and tables reported in the paper and the Supplementary Material

Datasets in included in the folder:
* gaa_results_football.xlsx: An Excel spreadsheet from Gavan Reilly’s website that contains the results from Gaelic football matches. 

* gaa_results_hurling.xlsx: An Excel spreadsheet from Gavan Reilly’s website that contains the results from hurling matches. 


The scripts were executed successfully with the following versions of the required packages (2018-09-17):

> sessionInfo()
R version 3.5.0 (2018-04-23)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_IE.UTF-8/en_IE.UTF-8/en_IE.UTF-8/C/en_IE.UTF-8/en_IE.UTF-8

attached base packages:
[1] tcltk     stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] nnet_7.3-12     ggeffects_0.3.2 effects_4.0-2   carData_3.0-1  
 [5] texreg_1.36.23  lme4_1.1-18-1   Matrix_1.2-14   rms_5.1-2      
 [9] SparseM_1.77    Hmisc_4.1-1     Formula_1.2-2   survival_2.41-3
[13] lubridate_1.7.4 cem_1.1.19      lattice_0.20-35 ggthemes_3.4.2 
[17] forcats_0.3.0   stringr_1.3.1   dplyr_0.7.6     purrr_0.2.5    
[21] readr_1.1.1     tidyr_0.8.1     tibble_1.4.2    ggplot2_3.0.0  
[25] tidyverse_1.2.1 rio_0.5.10     

loaded via a namespace (and not attached):
 [1] TH.data_1.0-8       minqa_1.2.4         colorspace_1.3-2   
 [4] modeltools_0.2-21   ggridges_0.5.0      sjlabelled_1.0.10  
 [7] estimability_1.3    snakecase_0.9.1     htmlTable_1.11.2   
[10] base64enc_0.1-3     rstudioapi_0.7      glmmTMB_0.2.0      
[13] MatrixModels_0.4-1  mvtnorm_1.0-7       coin_1.2-2         
[16] xml2_1.2.0          codetools_0.2-15    splines_3.5.0      
[19] mnormt_1.5-5        knitr_1.20          sjmisc_2.7.1       
[22] bayesplot_1.5.0     jsonlite_1.5        nloptr_1.0.4       
[25] broom_0.5.0         cluster_2.0.7-1     compiler_3.5.0     
[28] httr_1.3.1          emmeans_1.1.3       sjstats_0.14.2-3   
[31] backports_1.1.2     assertthat_0.2.0    lazyeval_0.2.1     
[34] survey_3.33-2       cli_1.0.0           acepack_1.4.1      
[37] htmltools_0.3.6     quantreg_5.35       tools_3.5.0        
[40] bindrcpp_0.2.2      coda_0.19-1         gtable_0.2.0       
[43] glue_1.2.0          Rcpp_0.12.18        cellranger_1.1.0   
[46] nlme_3.1-137        lmtest_0.9-36       psych_1.8.3.3      
[49] openxlsx_4.0.17     rvest_0.3.2         stringdist_0.9.4.7 
[52] polspline_1.1.12    MASS_7.3-49         zoo_1.8-1          
[55] scales_0.5.0        hms_0.4.2           parallel_3.5.0     
[58] sandwich_2.4-0      pwr_1.2-2           TMB_1.7.13         
[61] RColorBrewer_1.1-2  yaml_2.1.19         curl_3.2           
[64] gridExtra_2.3       rpart_4.1-13        latticeExtra_0.6-28
[67] stringi_1.2.4       randomForest_4.6-14 checkmate_1.8.5    
[70] rlang_0.2.2         pkgconfig_2.0.1     prediction_0.3.6   
[73] bindr_0.1.1         htmlwidgets_1.2     tidyselect_0.2.4   
[76] plyr_1.8.4          magrittr_1.5        R6_2.2.2           
[79] multcomp_1.4-8      combinat_0.0-8      pillar_1.2.1       
[82] haven_1.1.1         foreign_0.8-70      withr_2.1.2        
[85] modelr_0.1.1        crayon_1.3.4        grid_3.5.0         
[88] readxl_1.1.0        data.table_1.11.4   digest_0.6.15      
[91] xtable_1.8-2        stats4_3.5.0        MatchIt_3.0.2      
[94] munsell_0.4.3      